The invention relates generally to control systems and more particularly to deterministic optimization based control of systems.
Generally, control systems, such as an industrial plant or a power generation system, may be dynamic and include various constraints. For example, the constraints on the control system may be the result of actuator limits, operational constraints, economical restrictions, and/or safety restrictions. Accordingly, control of such a multivariable constrained dynamic system may be complex. Techniques such as coupled multi-loop proportional-integral-derivative (PID) controllers may not be best suited for handling the control of such complex control systems. On the other hand, one process control technique capable of handling the multivariable constraints is optimization based control (OBC). Specifically, OBC may improve the performance of the control system by enabling the system to operate closer to the various constraints (i.e., via dynamic optimization).
However, OBC may be computationally demanding because the dynamic optimization calculation may involve solving a constrained optimization problem such as quadratic programming (QP) problems at each sampling time. Utilizing a general solver may take seconds or even minutes. In addition, it may be difficult to predict the time it takes for the optimizer to solve the constrained optimization problems. Accordingly, to utilize OBC to control systems with faster dynamics, it may often be beneficial to enable deterministic OBC to provide a feasible control action within a predetermined control time.